Never did this before, so I was asking Q in the AWS docs how to do it.
It refused to help, as it didn't answer security related questions.
thank.
one of my questions about a login form also tripped a harassment flag
I suspect instead the people training these models have identified areas of questioning where their model is 99% right, but because the 1% wrong is incredibly costly they dodge the entire question.
Would you want your LLM to give out any legal advice, or medical advice, or can-I-eat-this-mushroom advice, if you knew due to imperfections in your training process, it sometimes recommended people put glue in their pizza sauce?
So sure, the LLM occasionally pranks someone, in a way similar to how random Internet posts do; it is confidently wrong, in a way similar to how most text on the Internet is confidently wrong because content marketers don't give a damn about correctness, that's not what the text is there for. As much as this state of things pains me, general population has mostly adapted.
Meanwhile, people who would appreciate a model that's 99% right on things where the 1% is costly, rightfully continue to ignore Gemini and other models by companies too afraid to play in the field for real.
A random person on the Internet often has surrounding context to help discern trustworthiness. A researcher can also query multiple sources to determine how much there is concensus about.
You can't do that with LLMs.
I cannot stress strongly enough that direct comparisons between LLMs and experts on the Internet are inappropriate.
In this context, I very much agree. But I'd like to stress that "experts on the Internet" is not what 99% of the users read 99% of the time, because that's not what search engines surface by default. When you make e.g. food or law or health-related queries, what you get back isn't written by experts - it's written by content marketers. Never confuse the two.
> A researcher can also query multiple sources to determine how much there is concensus about.
> You can't do that with LLMs.
A person like that will know LLMs hallucinate, and query multiple sources and/or their own knowledge, and/or even re-query the LLM several times. Such people are not in danger - but very much annoyed when perfectly reasonable queries get rejected on the grounds of "safety".